Skip to content

Minimum Viable Skills for Senior Researcher

The Minimum Viable Skillset for Senior Researchers focuses on Open Science (OS) activities and skills relevant for senior researchers. Senior researchers are typically defined as those who are established within their fields, developed a level of independence, and typically lead research projects. The profile highlights the role of Senior Researchers in setting the agenda by implementing OS policies, raising awareness, and mentoring and training Early Career Researchers in the principles of Open Science.

Organisational context:

  • Governmental organizations
  • National agencies
  • National funding organizations
  • Research Performing Organizations

Mission

Senior Researchers are key actors within institutional contexts in promoting Open Science and FAIR principles among research colleagues, and in supporting them ensuring that relevant data or other research outputs are made FAIR/Open in accordance with domain standards and stakeholder expectations. They are expected to be catalysts for change in how research is conducted by centering open science practices, and show leadership through implementing Open Science policies in their own research projects and teams, as well as their role in mentoring and training students, raising awareness of open science among undergraduate and masters students, and acting as a bridge between the scientific community and technical services. To achieve this mission, Senior Researchers are expected to possess an expert-level understanding of Open Science and FAIR principles and their applications in their discipline-specific contexts, including regulatory, ethical and policy requirements. In turn, they need to be supported by research organizations in this mission, in the form of Open Science policies and relevant resources to implement them.

OS Activities

  • Applies Open Science policies, strategies and best practices
  • Promotes and supports Open Science principles in their disciplinary fields by training other researchers in open science practices, methods and skills
  • Contributes to education and professional development of students and Early Career Researchers by developing curricula and programs in Open Science methods, including data management.
  • Provides researchers in their group with appropriate knowledge and support to understand regulatory, ethical and policy requirements affecting their research
  • Designs and manages research activities
  • Builds and coordinates research teams
  • Establishes collaboration networks

OS Outcomes

The main objective of the Senior Researcher is to conduct and oversee high quality and reproducible research, undertaken with integrity. Given their role in supervision, education, hiring, journal editing, peer review, and informing institutional policies, Senior Researchers can establish a research environment that supports and implements Open Science. Crucially, Senior Researchers have a responsibility to manage and nurture Early Career Researchers. This can be achieved via the following:

  • Advocating for and championing Open Science principles and policies in their institutions
  • Promoting education and training about open science skills, resources and solutions amongst other researchers and students
  • Integrating Open Science knowledge into their own teaching and research practices

Essential Skills and Competences

Technical skills and competences

  • Recognize discipline-specific Open Science principles and identify practices relevant to them at every stage of the research workflow.
  • Outline relevant practices of Open Science and FAIR principles create guidelines for their research teams.
  • Ability to identify and keep track of open research funding, and acquire funding that furthers Open Science goals through writing grants and funding applications.
  • Mentoring and training researchers and students in Open Science practices throughout the research life-cycle, and nurturing professional development of Early Career Researchers in accordance with Open Science principles.
  • Ability to build professional collaboration frameworks between academia and industry or other sectors to enable Open Science, build research projects that embed open science principles throughout.
  • Ability to collect, annotate and document data and software, create metadata, use relevant taxonomies, handle big data sets and use existing repositories.
  • Developing expert-level awareness of legal aspects related to Intellectual Property Rights (eg copyright, patents and trade secrets) and other Non-Personal Data (eg IoT data and research data), Personal Data Protection and Governance (eg processing Personal Data under the current legal framework, and managing data use agreements and policies on Data Protection), Privacy, and (Open) Licensing rules and frameworks, as well as the use of data and information which may be considered sensitive.
  • Developing expert-level awareness of ethical principles (eg transparency, diversity and accountability) and best practices (eg avoiding bias in data processing when using data-driven technologies) applicable to their field of expertise, including, but not limited to the general ethical principles, frameworks and codes of conduct applicable to research (eg the RRI Framework; the European Code of Conduct for Research Integrity);
  • Ability to balance (personal and non-personal) data protection requirements with Open Science/FAIR principles.
  • Applying open publication practices, such as publishing preprints, publishing in open access journals and platforms, ensuring data and code are available in open repositories to the extent possible.
  • Engaging with stakeholders outside academia to maximize research impact.

Soft/ transversal skills

  • Effective communication
  • Ability to provide constructive feedback
  • Research management and leadership
  • Time and people management
  • Teamwork and collaboration
  • Problem-solving
  • Research integrity

Link to any other MVS that this MVS is based on (from those in Skills4EOSC D2.1)

Reference sources

1 2 3 4 5 6 7 8 9 10

  1. Yuri Demchenko, Adam Belloum, Wouter Los, Tomasz Wiktorski, Andrea Manieri, Holger Brocks, Jana Becker, Dominic Heutelbeck, Matthias Hemmje, and Steve Brewer. Edison data science framework: a foundation for building data science profession for research and industry. In 2016 IEEE international conference on cloud computing technology and science (CloudCom), 620–626. IEEE, 2016. ↩

  2. Angus Whyte at al. Eoscpilot fair4s (skills and capability framework). 2018. URL: https://eoscpilot.eu/sites/default/files/eoscpilot-d7.3.pdf (visited on 2024-03-16). ↩

  3. European Commission, Directorate-General for Research, Innovation, N Manola, E Lazzeri, M Barker, I Kuchma, V Gaillard, and L Stoy. Digital skills for FAIR and Open Science – Report from the EOSC Executive Board Skills and Training Working Group. Publications Office, 2021. doi:doi/10.2777/59065. ↩

  4. European Commission, Directorate-General for Research, Innovation, C O'Carroll, B Hyllseth, R Berg, U Kohl, C Kamerlin, N Brennan, and G O’Neill. Providing researchers with the skills and competencies they need to practise Open Science. Publications Office, 2017. doi:doi/10.2777/121253. ↩

  5. Olivia S. Kowalczyk, Alexandra Lautarescu, Elisabet Blok, Lorenza Dall'Aglio, and Samuel J. Westwood. What senior academics can do to support reproducible and open research: a short, three-step guide. BMC Research Notes, 15(1):116, Mar 2022. URL: https://doi.org/10.1186/s13104-022-05999-0, doi:10.1186/s13104-022-05999-0. ↩

  6. LERU. Open science and its role in universities: a roadmap for cultural change. 2018. URL: https://www.leru.org/files/LERU-AP24-Open-Science-full-paper.pdf. ↩

  7. SKILLS FRAMEWORK – OBERRED. URL: https://oberred.eu/skills-framework/ (visited on 2024-03-16). ↩

  8. OECD. Building digital workforce capacity and skills for data-intensive science. 2020. URL: https://www.oecd-ilibrary.org/content/paper/e08aa3bb-en, doi:https://doi.org/https://doi.org/10.1787/e08aa3bb-en. ↩

  9. 070c564b-7c09-460f-8456-a0ac00e0526f. Vitae Researcher Development Framework and Researcher Development Statement: methodology and validation report 2012 — Vitae Website. URL: https://www.vitae.ac.uk/vitae-publications/rdf-related/researcher-development-framework-rdf-vitae-methodology-report-2012.pdf (visited on 2024-03-16). ↩

  10. A Whyte & K Ashley. Deliverable d7.1: skills landscape analysis and competence model. 2017. ↩